Distribution and Severity of Pasmo on Flax in North Dakota and Evaluation of Fungicides and Cultivars for Management
Bibliographic record
Abstract
Pasmo, caused by Septoria linicola, reduces flax (Linum usitatissimum) yield in the Canadian provinces of Manitoba and Saskatchewan, but little is known about its distribution and effect on yield in North Dakota. Field surveys for pasmo were conducted in 74 and 87 flax fields across 19 and 23 North Dakota counties in 2002 and 2003, respectively. The surveys indicated that pasmo was present in 17 and 18 counties in 2002 and 2003, respectively. County mean plant incidences ranged from 0 to 21% and 0 to 84.5% in 2002 and 2003, respectively. County mean pasmo severity ranged from 0 to 38.8% and 0 to 29.3% in 2002 and 2003, respectively. Significant (P ≤ 0.07) positive Pearson correlations were detected between total rainfall accumulated for June to August and pasmo severity in 2002 and 2003 and for rainfall and pasmo incidence in 2003. Field trials were conducted to determine the effect of fungicides and flax cultivars on pasmo severity and flax yield. Pasmo severity was significantly (P ≤ 0.05) reduced with azoxystrobin and sulfur fungicides compared with the untreated control. Flax yields were significantly (P ≤ 0.05) greater in azoxystrobin- and prothioconazole-treated plots than in the untreated control plots. Cv. Omega had significantly lower pasmo severity than the other three cultivars, but cv. Rahab 94 had the greatest yield of all the cultivars. Based on the results presented, pasmo is an important disease of flax in North Dakota, and its distribution is widespread throughout the flax-production region. Fungicides such as azoxystrobin and prothioconazole appear to be excellent potential tools for pasmo management.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".